CPE, qui signifie Common Platform Enumeration, est un système normalisé de dénomination du matériel, des logiciels et des systèmes d'exploitation. CPE fournit un schéma de dénomination structuré pour identifier et classer de manière unique les systèmes informatiques, les plates-formes et les progiciels sur la base de certains attributs tels que le fournisseur, le nom du produit, la version, la mise à jour, l'édition et la langue.
CWE, ou Common Weakness Enumeration, est une liste complète et une catégorisation des faiblesses et des vulnérabilités des logiciels. Elle sert de langage commun pour décrire les faiblesses de sécurité des logiciels au niveau de l'architecture, de la conception, du code ou de la mise en œuvre, qui peuvent entraîner des vulnérabilités.
CAPEC, qui signifie Common Attack Pattern Enumeration and Classification (énumération et classification des schémas d'attaque communs), est une ressource complète, accessible au public, qui documente les schémas d'attaque communs utilisés par les adversaires dans les cyberattaques. Cette base de connaissances vise à comprendre et à articuler les vulnérabilités communes et les méthodes utilisées par les attaquants pour les exploiter.
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Recherche de CVE id, CWE id, CAPEC id, vendeur ou mots clés dans les CVE
The replace_map_fd_with_map_ptr function in kernel/bpf/verifier.c in the Linux kernel before 4.5.5 does not properly maintain an fd data structure, which allows local users to gain privileges or cause a denial of service (use-after-free) via crafted BPF instructions that reference an incorrect file descriptor.
Informations du CVE
Métriques
Métriques
Score
Gravité
CVSS Vecteur
Source
V3.1
7.8
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
More informations
Base: Exploitabilty Metrics
The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component.
Attack Vector
This metric reflects the context by which vulnerability exploitation is possible.
Local
The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities.
Attack Complexity
This metric describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability.
Low
Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success when attacking the vulnerable component.
Privileges Required
This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability.
Low
The attacker requires privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources.
User Interaction
This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable component.
None
The vulnerable system can be exploited without interaction from any user.
Base: Scope Metrics
The Scope metric captures whether a vulnerability in one vulnerable component impacts resources in components beyond its security scope.
Scope
Formally, a security authority is a mechanism (e.g., an application, an operating system, firmware, a sandbox environment) that defines and enforces access control in terms of how certain subjects/actors (e.g., human users, processes) can access certain restricted objects/resources (e.g., files, CPU, memory) in a controlled manner. All the subjects and objects under the jurisdiction of a single security authority are considered to be under one security scope. If a vulnerability in a vulnerable component can affect a component which is in a different security scope than the vulnerable component, a Scope change occurs. Intuitively, whenever the impact of a vulnerability breaches a security/trust boundary and impacts components outside the security scope in which vulnerable component resides, a Scope change occurs.
Unchanged
An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Base: Impact Metrics
The Impact metrics capture the effects of a successfully exploited vulnerability on the component that suffers the worst outcome that is most directly and predictably associated with the attack. Analysts should constrain impacts to a reasonable, final outcome which they are confident an attacker is able to achieve.
Confidentiality Impact
This metric measures the impact to the confidentiality of the information resources managed by a software component due to a successfully exploited vulnerability.
High
There is a total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.
Integrity Impact
This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.
High
There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the impacted component.
Availability Impact
This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.
High
There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).
Temporal Metrics
The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence in the description of a vulnerability.
Environmental Metrics
These metrics enable the analyst to customize the CVSS score depending on the importance of the affected IT asset to a user’s organization, measured in terms of Confidentiality, Integrity, and Availability.
nvd@nist.gov
V2
7.2
AV:L/AC:L/Au:N/C:C/I:C/A:C
nvd@nist.gov
EPSS
EPSS est un modèle de notation qui prédit la probabilité qu'une vulnérabilité soit exploitée.
Score EPSS
Le modèle EPSS produit un score de probabilité compris entre 0 et 1 (0 et 100 %). Plus la note est élevée, plus la probabilité qu'une vulnérabilité soit exploitée est grande.
Date
EPSS V0
EPSS V1
EPSS V2 (> 2022-02-04)
EPSS V3 (> 2025-03-07)
EPSS V4 (> 2025-03-17)
2022-02-06
–
–
2.21%
–
–
2022-02-27
–
–
2.21%
–
–
2022-04-03
–
–
2.21%
–
–
2022-04-24
–
–
2.21%
–
–
2022-10-02
–
–
2.21%
–
–
2023-03-12
–
–
–
0.09%
–
2023-05-14
–
–
–
0.09%
–
2023-06-25
–
–
–
0.09%
–
2023-07-02
–
–
–
0.09%
–
2023-07-09
–
–
–
0.09%
–
2024-02-11
–
–
–
0.09%
–
2024-03-31
–
–
–
0.09%
–
2024-06-02
–
–
–
0.09%
–
2024-09-15
–
–
–
0.09%
–
2024-09-22
–
–
–
0.09%
–
2024-10-13
–
–
–
0.09%
–
2024-12-15
–
–
–
0.09%
–
2024-12-22
–
–
–
0.09%
–
2025-01-26
–
–
–
0.09%
–
2025-01-19
–
–
–
0.09%
–
2025-01-25
–
–
–
0.09%
–
2025-03-18
–
–
–
–
15.13%
2025-03-18
–
–
–
–
15.13,%
Percentile EPSS
Le percentile est utilisé pour classer les CVE en fonction de leur score EPSS. Par exemple, une CVE dans le 95e percentile selon son score EPSS est plus susceptible d'être exploitée que 95 % des autres CVE. Ainsi, le percentile sert à comparer le score EPSS d'une CVE par rapport à d'autres CVE.
Date de publication : 2016-05-03 22h00 +00:00 Auteur : Google Security Research EDB Vérifié : Yes
Source: https://bugs.chromium.org/p/project-zero/issues/detail?id=808
In Linux >=4.4, when the CONFIG_BPF_SYSCALL config option is set and the
kernel.unprivileged_bpf_disabled sysctl is not explicitly set to 1 at runtime,
unprivileged code can use the bpf() syscall to load eBPF socket filter programs.
These conditions are fulfilled in Ubuntu 16.04.
When an eBPF program is loaded using bpf(BPF_PROG_LOAD, ...), the first
function that touches the supplied eBPF instructions is
replace_map_fd_with_map_ptr(), which looks for instructions that reference eBPF
map file descriptors and looks up pointers for the corresponding map files.
This is done as follows:
/* look for pseudo eBPF instructions that access map FDs and
* replace them with actual map pointers
*/
static int replace_map_fd_with_map_ptr(struct verifier_env *env)
{
struct bpf_insn *insn = env->prog->insnsi;
int insn_cnt = env->prog->len;
int i, j;
for (i = 0; i < insn_cnt; i++, insn++) {
[checks for bad instructions]
if (insn[0].code == (BPF_LD | BPF_IMM | BPF_DW)) {
struct bpf_map *map;
struct fd f;
[checks for bad instructions]
f = fdget(insn->imm);
map = __bpf_map_get(f);
if (IS_ERR(map)) {
verbose("fd %d is not pointing to valid bpf_map\n",
insn->imm);
fdput(f);
return PTR_ERR(map);
}
[...]
}
}
[...]
}
__bpf_map_get contains the following code:
/* if error is returned, fd is released.
* On success caller should complete fd access with matching fdput()
*/
struct bpf_map *__bpf_map_get(struct fd f)
{
if (!f.file)
return ERR_PTR(-EBADF);
if (f.file->f_op != &bpf_map_fops) {
fdput(f);
return ERR_PTR(-EINVAL);
}
return f.file->private_data;
}
The problem is that when the caller supplies a file descriptor number referring
to a struct file that is not an eBPF map, both __bpf_map_get() and
replace_map_fd_with_map_ptr() will call fdput() on the struct fd. If
__fget_light() detected that the file descriptor table is shared with another
task and therefore the FDPUT_FPUT flag is set in the struct fd, this will cause
the reference count of the struct file to be over-decremented, allowing an
attacker to create a use-after-free situation where a struct file is freed
although there are still references to it.
A simple proof of concept that causes oopses/crashes on a kernel compiled with
memory debugging options is attached as crasher.tar.
One way to exploit this issue is to create a writable file descriptor, start a
write operation on it, wait for the kernel to verify the file's writability,
then free the writable file and open a readonly file that is allocated in the
same place before the kernel writes into the freed file, allowing an attacker
to write data to a readonly file. By e.g. writing to /etc/crontab, root
privileges can then be obtained.
There are two problems with this approach:
The attacker should ideally be able to determine whether a newly allocated
struct file is located at the same address as the previously freed one. Linux
provides a syscall that performs exactly this comparison for the caller:
kcmp(getpid(), getpid(), KCMP_FILE, uaf_fd, new_fd).
In order to make exploitation more reliable, the attacker should be able to
pause code execution in the kernel between the writability check of the target
file and the actual write operation. This can be done by abusing the writev()
syscall and FUSE: The attacker mounts a FUSE filesystem that artificially delays
read accesses, then mmap()s a file containing a struct iovec from that FUSE
filesystem and passes the result of mmap() to writev(). (Another way to do this
would be to use the userfaultfd() syscall.)
writev() calls do_writev(), which looks up the struct file * corresponding to
the file descriptor number and then calls vfs_writev(). vfs_writev() verifies
that the target file is writable, then calls do_readv_writev(), which first
copies the struct iovec from userspace using import_iovec(), then performs the
rest of the write operation. Because import_iovec() performs a userspace memory
access, it may have to wait for pages to be faulted in - and in this case, it
has to wait for the attacker-owned FUSE filesystem to resolve the pagefault,
allowing the attacker to suspend code execution in the kernel at that point
arbitrarily.
An exploit that puts all this together is in exploit.tar. Usage:
user@host:~/ebpf_mapfd_doubleput$ ./compile.sh
user@host:~/ebpf_mapfd_doubleput$ ./doubleput
starting writev
woohoo, got pointer reuse
writev returned successfully. if this worked, you'll have a root shell in <=60 seconds.
suid file detected, launching rootshell...
we have root privs now...
root@host:~/ebpf_mapfd_doubleput# id
uid=0(root) gid=0(root) groups=0(root),4(adm),24(cdrom),27(sudo),30(dip),46(plugdev),113(lpadmin),128(sambashare),999(vboxsf),1000(user)
This exploit was tested on a Ubuntu 16.04 Desktop system.
Fix: https://git.kernel.org/cgit/linux/kernel/git/torvalds/linux.git/commit/?id=8358b02bf67d3a5d8a825070e1aa73f25fb2e4c7
Proof of Concept: https://bugs.chromium.org/p/project-zero/issues/attachment?aid=232552
Exploit-DB Mirror: https://gitlab.com/exploit-database/exploitdb-bin-sploits/-/raw/main/bin-sploits/39772.zip
Products Mentioned
Configuraton 0
Linux>>Linux_kernel >> Version From (including) 4.4 To (excluding) 4.4.11